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  • 标题:Built environment data modelling: a review of current approaches and standards supporting Asset Management
  • 本地全文:下载
  • 作者:Nicola Moretti ; Xiang Xie ; Jorge Merino Garcia
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2022
  • 卷号:55
  • 期号:19
  • 页码:229-234
  • DOI:10.1016/j.ifacol.2022.09.212
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractInformation Management is crucial in the Asset Management domain. Well-structured information management processes allow to access the needed data, in the right format, and enables the development of cross-domain Asset Management services. Several studies can be found in literature, on the capabilities and applications of digital tools in Architecture Constructions and Operations (AECO), demonstrating how digitisation has changed the traditional processes. Moreover, many data modelling approaches and standards can be used to support digital Asset Management applications. Due to the advancement of Digital Twin related research, the interest for the ontological and data modelling approaches have increased in recent years. This article aims at organising the body of knowledge on data modelling in AECO, through a critical review of existing approaches and standards. The literature is studied and the main trends are highlighted. The most relevant articles are selected and a contents analysis is carried out. The study shows that digital Asset Management applications require interdisciplinarity and data access across different domain; two main approaches for the development of intermediate data models can be identified in literature and a unique data model able to represent multiple scales and domains cannot be found. Thus, some future research works are proposed as a conclusion of the literature review.
  • 关键词:KeywordsData ModellingInformation ManagementAsset ManagementAECObuilt environmentdigital twin
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